科普文章，美国股票，大泡沫

Core Insights - The article discusses historical bubbles in the U.S. stock market, highlighting the patterns and consequences of these events, particularly focusing on the current AI hype as a potential bubble [1][2][3][4]. Historical Bubbles - The 1920s bubble led to the Great Depression, with the Dow Jones Industrial Average increasing over six times from 1921 to 1929, while wages remained stagnant and wealth inequality soared [1]. - The dot-com bubble in 2000 saw the Nasdaq index rise fourfold in five years, with a peak P/E ratio of 200, followed by a 78% crash [2]. - The 2008 financial crisis was driven by a housing bubble, where banks issued loans to unqualified borrowers, leading to the collapse of Lehman Brothers and a global financial crisis [2]. Current AI Hype - The current AI trend is compared to past bubbles, with Nvidia's market cap reaching $3 trillion and venture capital investments in AI startups exceeding $192.7 billion, representing over half of total venture capital [2][3]. - Research indicates that 95% of organizations investing in AI have not seen any returns, raising concerns about the sustainability of the current AI investment landscape [2][3]. Capital Dynamics - The article highlights a "circular revenue" game among tech giants, where investments are recycled within the ecosystem, raising questions about genuine demand [3]. - Historical patterns suggest that when the Federal Reserve raises interest rates above 5%, it often triggers a crisis, with predictions that the AI bubble may burst between late 2026 and early 2027 [3]. Investment Philosophy - The article emphasizes that asset prices must eventually return to their intrinsic value, and that every bubble is cloaked in the guise of a "new era" [3]. - It stresses the importance of understanding risks and focusing on sustainable customer demand rather than getting caught up in capital loops created by major companies [3][4].